Opus 4.1 API Pricing
Opus 4.1 costs $15.00 per 1M input tokens and $75.00 per 1M output tokens on Anthropic's API. Cached input is billed at $1.50 per 1M tokens. Prices are provider list prices in USD, refreshed as sources update; see the Opus 4.1 model profile for capability scores.
Price List
| Rate | Price (USD) | Notes |
|---|---|---|
| Input | $15.00 | per 1M tokens |
| Output | $75.00 | per 1M tokens |
| Cached input (read) | $1.50 | per 1M tokens |
| Cache write | $18.75 | per 1M tokens |
| Cache write (1-hour) | $30.00 | per 1M tokens |
| Blended input + output | $90.00 | 1M in + 1M out at list price |
What a Workload Costs
Computed straight from the list prices above — token counts are illustrative workload sizes, not measurements of Opus 4.1.
| Workload | Cost | Tokens |
|---|---|---|
| Short chat turn | $0.052 | 1K in / 500 out |
| Summarize a long document | $1.65 | 100K in / 2K out |
| Agentic coding session | $15.00 | 500K in / 100K out |
| 1M input + 1M output tokens | $90.00 | 1M in / 1M out |
Effective Cost
In AI IQ's scoring, Opus 4.1's list price is adjusted by a token-usage multiplier of 0.396, giving an effective cost of $35.63 per 1M input + output tokens. That places it #132 of 143 models on the effective-cost ranking (lower is cheaper). Some models spend far more tokens than others on the same task, so effective cost compares what a unit of work really costs. Method details are on the methodology page; see all models on the cost charts and the falling cost of intelligence over time.
Cheaper Alternatives at Similar Capability
Models with a lower effective cost that score within a few IQ points of Opus 4.1 (IQ 98), or better.
| Model | Provider | IQ | Effective Cost / 1M |
|---|---|---|---|
| gpt-6-astra | OpenAI | 142 | $34.18 |
| gpt-6.1-sol | OpenAI | 139 | $11.09 |
| gpt-6-sol | OpenAI | 138 | $9.87 |
| gpt-5.6-sol | OpenAI | 136 | $27.44 |
| Gemini 3.8 Flash | 132 | $8.02 | |
| gpt-5.6-terra | OpenAI | 131 | $13.75 |